A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot

  • Ahmed S. Al-Araji Department of Control and Systems Engineering/ University of Technology
  • Noor Q. Yousif Department of Control and Systems Engineering/ University of Technology
Keywords: Bees Algorithm, Nonlinear Controller, Matlab Package, Particle Swarm Optimization, Wheeled Mobile Robots.

Abstract

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is more accurate in terms of fast on-line finding and tuning  parameters of the controller lead to obtaining smoothness with small spikes control action as well as minimizing tracking pose error of the wheeled mobile robot than the performance of nonlinear back-stepping technique.

 

Keywords: Bees Algorithm, Nonlinear Controller, Matlab Package, Particle Swarm Optimization, Wheeled Mobile Robots.

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Published
2017-09-30
How to Cite
Al-Araji, A., & Yousif, N. (2017). A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot. Al-Khwarizmi Engineering Journal, 13(3), 64-73. Retrieved from https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/360
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Articles